Machine Learning · head to head
Dataiku vs Dynatrace

Dynatrace
Logging
Application Performance Management and Observability
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Dataiku no pricing is published at any tier, and the plans page carries no figures at all; Dynatrace pricing is commitment based: rates require an annual platform level commitment rather than month to month purchase
- They diverge on capability: Dataiku covers Visual data prep, Dynatrace covers AI-powered analytics.
Where they differ
Only the attributes on which Dataiku and Dynatrace actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Dataiku
- Visual data prep
- AutoML
- MLOps
- Collaboration
- Governence
- Python
- R
- Spark
Only in Dynatrace
- AI-powered analytics
- APM
- Infrastructure monitoring
- Log analysis
- API
- Webhooks
- REST
- Api support
Both cover
- Web support
What people use each for
The jobs each tool is most often brought in to do.
Dataiku
- Building and deploying data science and machine learning pipelinesnot Dynatrace
- Giving analysts and data scientists a shared visual and code environmentnot Dynatrace
Dynatrace
- Full stack application performance monitoring with automatic dependency discoverynot Dataiku
- Kubernetes and container platform observability priced per podnot Dataiku
- Log ingest, processing and query analyticsnot Dataiku
- Real user monitoring and session replay for web applicationsnot Dataiku
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Dataiku
- No pricing is published at any tier, and the plans page carries no figures at all
- User, row and compute limits are not stated, so nothing about scale can be assessed before contacting sales
- Access begins with a demo request or a trial rather than a self serve signup
Dynatrace
- Pricing is commitment based: rates require an annual platform level commitment rather than month to month purchase
- Full-Stack Monitoring is priced at $58 per month per 8 GiB of host memory, so a 64 GiB host counts as eight units
- Infrastructure Monitoring at $29 per host per month excludes code level tracing, which requires Full-Stack
- Session Replay doubles Real User Monitoring cost from $2.25 to $4.50 per 1,000 sessions
- Runtime Vulnerability Analytics and Runtime Application Protection are each charged separately at $13 per month per 8 GiB host on top of monitoring
Pricing, plan by plan
Dataiku
Free- Free EditionFree
- Single user
- Core features
- EnterpriseFree
- Full platform
- Collaboration
- MLOps
Dynatrace
Free- FreeFree
- AI-powered analytics
- APM
- Infrastructure monitoring
Which should you pick?
Choose Dataiku if
- You need visual data prep.
- You want to start without paying.
- You work on Linux, Mac, Windows, Web.
- You also want automl.
Choose Dynatrace if
- You need ai-powered analytics.
- You want to start without paying.
- You work on Web, Api.
- You also want apm.
Questions people ask
- Is Dataiku or Dynatrace better?
- Neither clearly leads. Dataiku starts at Free and Dynatrace at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dataiku or Dynatrace?
- Dataiku starts at Free and Dynatrace at Free.
- Does Dataiku or Dynatrace run on more platforms?
- Dataiku runs on Linux, Mac, Windows, Web. Dynatrace runs on Web, Api.
- Can I use Dataiku for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Dataiku best used for?
- Dataiku is most often used for building and deploying data science and machine learning pipelines, giving analysts and data scientists a shared visual and code environment. Of those, building and deploying data science and machine learning pipelines and giving analysts and data scientists a shared visual and code environment are not what Dynatrace is typically brought in for.
- What can Dataiku do that Dynatrace cannot?
- Dataiku covers Visual data prep, AutoML, MLOps, Collaboration. Dynatrace covers AI-powered analytics, APM, Infrastructure monitoring, Log analysis. Both handle Web support.
Answered from the vendors’ own pages
Dataiku: What are Dataiku pricing tiers and costs?
Dataiku pricing information is not available on their public website. Customers must contact Dataiku sales directly to request pricing, trial access, and licensing information.
SourceDynatrace: What is the pricing model for Dynatrace monitoring?
Dynatrace uses commitment-based platform subscription pricing with a minimum annual commitment at the platform level. You pay no per-capability or per-user fees. All capabilities are included day one and draw from your commitment at published rates.
SourceDataiku: Does Dataiku offer a free tier or trial?
Free tier or trial availability for Dataiku cannot be determined from publicly accessible pages. Contact Dataiku directly to inquire about evaluation options.
SourceDynatrace: Is there an overage charge if I exceed my commitment?
No, there are no overage penalties. Excess usage continues at the same per-unit rates published on the rate card. The more you commit upfront, the deeper your discount.
SourceDynatrace: What is the cost for monitoring application infrastructure?
Application monitoring costs $7/month per host ($0.01/hour) for Foundation & Discovery, $29/month per host for Infrastructure Monitoring, or $58/month per 8 GiB of host memory for Full-Stack Monitoring.
SourceDynatrace: How much does log ingestion and querying cost?
Log Analytics pricing is $0.20/GiB for ingestion, then either $0.0007/GiB-day for retention with bundled queries (10-35 days retention included), or pay-per-query at $0.0007/GiB-day retention plus $0.0035 per GiB scanned.
SourceDynatrace: Is there a free trial available?
Yes, Dynatrace offers a 15-day free trial plus a sandbox environment for hands-on exploration at no cost.
SourceRelated pages
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- Dynatrace vs TensorFlow
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- Dynatrace vs Jupyter
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- Dynatrace vs PyTorch
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- Dynatrace vs Apache Spark MLlib
- Dynatrace vs Weaviate
- Dynatrace vs Weights & Biases
- Dynatrace vs Alteryx
- Dynatrace vs Elastic Stack
- Dynatrace vs New Relic
- Dynatrace vs Datadog Logs
- Dynatrace vs Coralogix
- Dynatrace vs Grafana Loki
- Dynatrace vs incident.io
- Dynatrace vs Cronitor
- Dynatrace vs FireHydrant
- Dynatrace vs Healthchecks
- Dynatrace vs Openstatus
- Dynatrace vs Rootly
- Dynatrace vs Checkly
- Dynatrace vs CloudWatch
- Dynatrace vs InfluxDB
- Dynatrace vs Airbrake
- Dynatrace vs AppDynamics
- Dynatrace vs Axiom
- Dynatrace vs Azure Monitor

